Paper Info
Title
Visualization of Noisy and Biased Volume Data Using First and Second Order Derivative Techniques
Abstract
The quality of volume visualization depends strongly on the quality of the underlying data. In virtual colonoscopy, CT data should be acquired at a low radiation dose that results in a low signal-to-noise ratio. Alternatively, MRI data is acquired without ionizing radiation, but suffers from noise and bias (global signal fluctuations). Current volume visualization techniques often do not produce good results with noisy or biased data. This paper describes methods for volume visualization that deal with these imperfections. The techniques are based on specially adapted edge detectors using first and second order derivative filters. The filtering is integrated into the the visualization process. The first order derivative method results in good quality images but suffers from localization bias. The second order method has better surface localization, especially in highly curved areas. It guarantees minimal detail smoothing resulting in a better visualization of polyps.
Year
DOI
Venue
2003
10.1109/VISUAL.2003.1250397
IEEE Visualization 2003
Keywords
Field
DocType
order derivative filter,better visualization,biased volume data,second order derivative techniques,visualization process,current volume visualization technique,volume visualization,good quality image,order derivative method result,underlying data,ct data,mri data,second order,visualization,data visualisation,first order,radiation dose,data visualization,signal to noise ratio,mri,signal filtering,ionizing radiation,medical imaging
Computer vision,Data visualization,Second derivative,Computer science,Visualization,Signal-to-noise ratio,Filter (signal processing),Smoothing,Artificial intelligence,Virtual colonoscopy,Detector
Conference
ISBN
Citations 
PageRank 
0-7695-2030-8
5
0.69
References 
Authors
7
5
Name
Order
Citations
PageRank
M. P. Persoon150.69
Iwo Serlie21218.81
Frits H. Post3184.00
Roel Truyen421819.37
F M Vos5536.23